Recently, there has been an increased interest on applying data augmentation techniques on sentence-level NLP tasks, such as text classification [1]}, , natural language inference [2]}, and machine translation [3]}. Augmentation methods explored for these tasks include creating augmented instances by manipulating a few words in the original instance, such as word replacement , [4]}, [5]}, random deletion [1]}, and word position swap [7]}, [2]}; or creating entirely artificial instances via generative models, such as variational autoencoders , [9]} and back-translation models , [10]}.
